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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ganesan, Ezhilarasan
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Computer Science & IT Engineering

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A novel approach to wastewater treatment control: A self-organizing fuzzy sliding mode controller Kumara, Varuna; Ganesan, Ezhilarasan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2796-2807

Abstract

The treatment of wastewater plays a crucial role in protecting the environment and ensuring the sustainable use of resources. This research paper presents a new methodology for managing wastewater treatment operations, utilising Self-Organizing Fuzzy Sliding Mode Controller (SOFSMC) to enhance the efficiency of treatment procedures. MATLAB Simulink functions as a simulation tool that facilitates meticulous analysis. SOFSMC presents a control strategy that is both adaptive and robust. This strategy effectively regulates crucial parameters, including dissolved oxygen levels, pH levels, and flow rates. It achieves this within the challenging and complex framework of wastewater treatment, which is characterised by dynamic and nonlinear dynamics. Using a SOFSMC for wastewater treatment control is novel approach. This novel technique creates a self-learning, dynamic system using fuzzy logic (FL) and sliding mode control (SMC). This unique approach can autonomously adapt to wastewater treatment processes' complex and nonlinear dynamics, improving efficiency, resource optimisation, and system dependability. The results emphasise the potential of SOFSMC as a revolutionary approach for wastewater treatment. This approach can improve treatment effectiveness, conserve resources, and protect the environment. The proposed method SOFSMC, exhibits commendable outcomes, with an integrated absolute error of 0.082 mg/L, an integrated square differential error of 0.091 mg/L, and a response time of 1.85 seconds This study offers a substantial advancement in the field of wastewater treatment regulation, highlighting its significance in the context of sustainable water management and environmental conservation.
Optimized robust fuzzy sliding mode control for efficient wastewater treatment: a comprehensive study Kumara, Varuna; Ganesan, Ezhilarasan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp631-638

Abstract

Wastewater treatment plants (WWTPs) are plagued by nonlinearities, uncertainties, and disturbances that degrade control performance and may even lead to severe instability. The WWTP control issue has received a lot of research and development during the last several decades. One well-known way of designing a resilient control system is called sliding mode control (SMC). The SMC's greatest strength lies in its innate resistance to disturbances and uncertainty. Incorporating fuzzy SMC would eliminate the chattering effect, the primary drawback of traditional sliding-mode controller, without sacrificing robustness against parametric uncertainties, modeling errors, and variable dynamic loads. This article discusses the hybridization of fuzzy logic with sliding mode control to provide highly excellent stability and accuracy in a control system. As a means of optimizing the fuzzy SMC, the gradient-free optimization technique known as the Jaya algorithm is investigated. By repeatedly altering a population of individual solutions, this population-based method can deal with both limited and unbounded optimization issues.
Co-Authors Kumara, Varuna